Machine Learning Innovations in CPR: A Comprehensive Survey on Enhanced Resuscitation Techniques

TL;DR

This survey reviews how machine learning and AI are revolutionizing CPR by improving techniques, devices, and data analysis, leading to better resuscitation outcomes and highlighting future research directions.

Contribution

It provides a comprehensive overview and critical analysis of current ML-driven CPR methods, classification, challenges, and future prospects.

Findings

ML enhances predictive accuracy in CPR outcomes

AI-integrated devices improve real-time resuscitation support

Significant potential for future ML applications in CPR

Abstract

This survey paper explores the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in Cardiopulmonary Resuscitation (CPR). It examines the evolution from traditional CPR methods to innovative ML-driven approaches, highlighting the impact of predictive modeling, AI-enhanced devices, and real-time data analysis in improving resuscitation outcomes. The paper provides a comprehensive overview, classification, and critical analysis of current applications, challenges, and future directions in this emerging field.